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. 2024 Aug 2;10(16):e35489.
doi: 10.1016/j.heliyon.2024.e35489. eCollection 2024 Aug 30.

Integrating network analysis and experimental validation to reveal the mechanism of si-jun-zi decoction in the treatment of renal fibrosis

Affiliations

Integrating network analysis and experimental validation to reveal the mechanism of si-jun-zi decoction in the treatment of renal fibrosis

Xinxin Yu et al. Heliyon. .

Abstract

Treating kidney diseases from the perspective of spleen is an important clinical method in traditional Chinese medicine (TCM) for anti-renal fibrosis (RF). Si-jun-zi decoction (SJZD), a classic formula for qi-invigorating and spleen-invigorating, has been reported to alleviate RF. This study aims to investigate the potential mechanism by which SJZD attenuates RF. The results demonstrated notable improvements in renal function levels, inflammation and fibrosis indices in UUO-mice following SJZD intervention. The main active ingredients identified were Quercetin, Kaempferol, Naringenin and 7-Methoxy-2-methyl isoflavone. Furthermore, STAT3, MAPK3, MYC were confirmed as key targets. Additionally, GO enrichment analysis demonstrated that SJZD delayed RF primarily by regulating oxidative stress and other biological mechanisms. KEGG enrichment analysis revealed the involvement of pathways such as Lipid and atherosclerosis signaling pathway, MAPK signaling pathway and other pathways in the reno-protective effects of SJZD. The molecular docking results revealed that the active ingredients of SJZD were well-bound and stable to the core targets. The experiments results revealed that Quercetin, Kaempferol, and Naringenin not only improved the morphology of TGF-β-induced HK-2 cells but also reversed the expression of α-SMA, COL1A1 and MAPK, thereby delaying the progression of RF. The anti-RF effects of SJZD were exerted through multi-components, multi-targets and multi-pathways.

Keywords: Experimental validation; Molecular docking; Network pharmacology; Renal fibrosis; Si-jun-zi decoction.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
(A) The composition and proportion of the herbs in SJZD. (B) The workflow of the entire research design.
Fig. 2
Fig. 2
The levels of BUN (A) and SCr (B) in UUO-mice. (C) Representative micrographs of renal tissues with H&E and Masson trichrome staining. (D) The renal tubulointerstitial injury index was scored according to H&E staining. (E) Percentage of positive Masson staining in the renal tubulointerstitial region relative to the entire region. Data are represented as mean ± SD. Superscript letters *, ** and *** denoted P < 0.05, P < 0.01 and P < 0.001, respectively.
Fig. 3
Fig. 3
(A) RF-related potential targets from 4 databases. (B) The intersection gene targets of RF and SJZD.
Fig. 4
Fig. 4
(A) F–H–C-T-D network. The representatives of V nodes indicate gene targets of RF. The diamond nodes stand for active components. The red line indicated that Kaempferol came from both Gancao and Renshen. (B) C-T network. The representatives of V nodes indicate gene targets of RF. Different colors of the pie chart display that the components are from different Chinese herbs, red figures Gancao, green shows Renshen, blue represents Fuling and yellow demonstrates Baizhu. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5
Fig. 5
(A) PPI network. (a) PPI network. It comprises 159 nodes and 1,512 edges. Each node represents relevant targets, and edges stand for protein-protein associations. (b) PPI network imported from String database to Cytoscape 3.7.0. (c) Sub-network of significant targets extracted from (b) by filtering 6 parameters: BC, CC, DC, EC, NC and LAC. This network is made up of 45 nodes and 608 edges. (d) Sub-network of more significant targets extracted from (c) by filtering 6 parameters: BC, CC, DC, EC, NC and LAC. This network is made up of 17 nodes and 194 edges. (e) Sub-network of core targets extracted from (d) by filtering 6 parameters: BC, CC, DC, EC, NC and LAC. This network is made up of 3 nodes and 6 edges. (B) Topology parameter values of core targets.
Fig. 6
Fig. 6
(A)The top 10 GO-terms of BP/CC/MF for SJZD anti-RF and GO-terms of mitochondrial function. (B) Targets involved in the top 10 mitochondrial function. (C) Core targets among the top 10 significantly enriched GO terms in BP, CC and MF.
Fig. 7
Fig. 7
(A) KEGG analysis of the top 30 target gene enrichment signaling pathways of SJZD associated with RF target genes. (B) The top 30 target gene enrichment signaling pathways network. The pink diamond nodes represent signaling pathways, and the representatives of purple V nodes indicate gene targets of RF. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 8
Fig. 8
(A) Heat map of the docking results for the main active ingredients and the key targets. (B) Molecular docking, MAPK3 (3R1N/3FXW/7NRB)-Quercetin, MAPK3 (3R1N/3FXW/7NRB)-Kaempferol, MAPK3 (3R1N/3FXW/7NRB)-Naringenin.
Fig. 9
Fig. 9
Cell Viability. Cell viability with different concentrations of Quercetin (A), Kaempferol (B), and Naringenin (C). After induced with TGF-β, Cell viability with different concentrations of Quercetin (D), Kaempferol (E), and Naringenin (F). Data are represented as mean ± SD. Superscript letters #, ## and ### denoted relative to control group P < 0.05, P < 0.01 and P < 0.001, respectively. Superscript letters *, ** and *** are denoted relative to model group P < 0.05, P < 0.01 and P < 0.001, respectively.
Fig. 10
Fig. 10
(A) Cell morphology. Bar = 50 μm. Immunofluorescence images for the protein expression of α-SMA, COL1A1. Bar = 20 μm. (B) Statistical graph of protein expression levels of α-SMA and COL1A1. Data are represented as mean ± SD. (C) Statistical graph for mRNA expression levels of α-SMA and COL1A1. Data are represented as mean ± SD. Superscript letters #, ## and ### denoted relative to control group P < 0.05, P < 0.01 and P < 0.001, respectively. Superscript letters ** and *** are denoted relative to model group P < 0.01 and P < 0.001, respectively.
Fig. 11
Fig. 11
(A) Representative immunofluorescence images for the protein expression of MAPK. Bar = 20 μm. (B) Statistical graph for protein expression levels of MAPK. Data are represented as mean ± SD. Superscript letters ## and ### denoted relative to control group P < 0.01 and P < 0.001, respectively. Superscript letters ** and *** are denoted relative to model group P < 0.01 and P < 0.001, respectively.
Fig. 12
Fig. 12
Scatterplot matrix of within-group Pearson correlation analysis of Quercetin (A), Kaempferol (B) and Naringenin (C). Superscript letters *** denoted relative to model group P < 0.001.

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